• 杨霖

  • 职称:

    讲师

  • 职务:

  • 主讲课程:

    统计学

  • 研究方向:

    统计学

  • 办公室:

  • 电子邮件:

    yang.lin@fzu.edu.cn

基本信息:

杨霖,女,硕士生导师。

    

教育及工作经历:

2014/08--至今, 福州大学,讲师

2011/08--2014/02 法国曼恩大学,获博士学位

2008/09--2010/11 法国曼恩大学,获硕士学位

2004/09--2008/06 山东大学,获学士学位

科研项目:

1.福建省教育厅中青年教师教育科研项目,基于泊松过程变点模型的假设检验及修正检验,2019/12-2022/050.5万,主持

2.国家自然科学基金面上项目,基于视频表示学习的时空模型研究及其应用,2020/10-2024/1267.6万,参加

3.国家自然科学基金面上项目,可分离非线性优化问题研究及其应用,2020/10-2024/1268.44万,参加

4.福建省自然科学基金项目,判别检验理论及其在泊松过程参数模型的应用, 2021/11-2024/114万,主持

主要论著:

1. S. Dachian*; L. Yang; On a Poissonian change-point model with variable jump size, Statistical Inference for Stochastic Processes, 2015, 18(2): 127-150.

2. S. Dachian; Yu A. Kutoyants; L. Yang*; On hypothesis testing for Poisson processes: Regular case, Communications in Statistics-Theory and Methods, 2016, 45(23):6816-683.

3. S. Dachian; Yu A. Kutoyants; L. Yang*; On hypothesis testing for Poisson processes: Singular cases, Communications in Statistics -Theory and Methods, 2016, 45(23): 6833-6859.

4. S. Dachian; L. Yang*; Simultaneous Testing of Change-Point Location and of a Regular Parameter by Poisson Observations, Statistical Inference for Stochastic Processes, 2020, 23:465-487.

5. C.Y. Zhang; J.F. Hu*; L. Yang*; C.L. P. Chen; Z.L. Yao; Graph deconvolutional networks, Information Sciences, 2020, 518: 330-340.

6. 林楠,杨霖*. 基于泊松过程尖点模型的修正假设检验. 统计与决策,2021(14): 16-19.

7. L. Yang*; Multiple hypothesis testing for Poisson processes with variable change–point intensity, Communications in Statistics-Theory and Methods, 2022, 51(3):744-766.

学术报告:

1. Lin Yang; Some examples of the hypothesis testing for Poisson processes, Asymptotical Statistics of Stochastic Processes IX, Poster, Le Mans,France,2013.03.11-03.14.

2. Lin Yang; Hypothesis testing on Poissonian model in non regular situation, Asymptotical Statistics of Stochastic Processes X, Poster, Le Mans, ,France,2015.03.17-03.20.

3. Serguei Dachian, Lin Yang; Estimation and Testing of a Small Change Location in the Intensity of a Poisson Process, Robust Statistics and Financial Mathematics-2018, Tomsk, Russia, 2018.07.09-07.11.